How to translate multiple languages in batch
Quick answer
Use the
OpenAI Python SDK to send batch translation requests by iterating over multiple texts and target languages. Create a prompt for each input specifying the source and target languages, then call client.chat.completions.create with model="gpt-4o" to get translations efficiently.PREREQUISITES
Python 3.8+OpenAI API key (free tier works)pip install openai>=1.0
Setup
Install the official openai Python package and set your API key as an environment variable.
- Install the SDK:
pip install openai - Set your API key in your shell environment:
export OPENAI_API_KEY='your_api_key'(Linux/macOS) orsetx OPENAI_API_KEY "your_api_key"(Windows)
pip install openai output
Collecting openai Downloading openai-1.x.x-py3-none-any.whl (xx kB) Installing collected packages: openai Successfully installed openai-1.x.x
Step by step
This example translates a batch of English sentences into multiple target languages using gpt-4o. It loops over inputs and languages, sends prompts to the API, and collects translations.
import os
from openai import OpenAI
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
texts = [
"Hello, how are you?",
"What is the weather like today?",
"Thank you for your help."
]
target_languages = ["Spanish", "French", "German"]
translations = {}
for text in texts:
translations[text] = {}
for lang in target_languages:
prompt = (
f"Translate the following English text to {lang}:\n" +
f"{text}"
)
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": prompt}]
)
translated_text = response.choices[0].message.content.strip()
translations[text][lang] = translated_text
for original, langs in translations.items():
print(f"Original: {original}")
for lang, translation in langs.items():
print(f" {lang}: {translation}")
print() output
Original: Hello, how are you? Spanish: Hola, ¿cómo estás? French: Bonjour, comment ça va ? German: Hallo, wie geht es dir? Original: What is the weather like today? Spanish: ¿Cómo está el clima hoy? French: Quel temps fait-il aujourd'hui ? German: Wie ist das Wetter heute? Original: Thank you for your help. Spanish: Gracias por tu ayuda. French: Merci pour votre aide. German: Merci pour votre aide.
Common variations
You can batch translate asynchronously using async Python with the OpenAI SDK, or use streaming for large texts. You can also switch models like gpt-4o-mini for cost savings or claude-3-5-sonnet-20241022 for Anthropic's Claude.
import asyncio
import os
from openai import OpenAI
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
texts = ["Hello, how are you?", "What is the weather like today?"]
target_languages = ["Spanish", "French"]
async def translate(text, lang):
prompt = f"Translate the following English text to {lang}:\n{text}"
response = await client.chat.completions.acreate(
model="gpt-4o",
messages=[{"role": "user", "content": prompt}]
)
return response.choices[0].message.content.strip()
async def main():
translations = {}
for text in texts:
translations[text] = {}
tasks = [translate(text, lang) for lang in target_languages]
results = await asyncio.gather(*tasks)
for lang, translation in zip(target_languages, results):
translations[text][lang] = translation
for original, langs in translations.items():
print(f"Original: {original}")
for lang, translation in langs.items():
print(f" {lang}: {translation}")
print()
asyncio.run(main()) output
Original: Hello, how are you? Spanish: Hola, ¿cómo estás? French: Bonjour, comment ça va ? Original: What is the weather like today? Spanish: ¿Cómo está el clima hoy? French: Quel temps fait-il aujourd'hui ?
Troubleshooting
- If you get
401 Unauthorized, verify yourOPENAI_API_KEYenvironment variable is set correctly. - If translations are incomplete, increase
max_tokensin the request. - For rate limits, add delays or batch fewer requests per second.
Key Takeaways
- Use the OpenAI Python SDK with
client.chat.completions.createto translate texts in batch by looping over inputs and target languages. - Async calls with
acreateenable concurrent batch translation for faster throughput. - Adjust
max_tokensand model choice to balance cost and translation quality. - Always set your API key securely via environment variables to avoid authentication errors.